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This app for watching Python tutorials for learning Python programming language.This app providing the functionality for easy to learn and working with very powerful and simple programming language Python. In this app we are providing two language tutorials Hindi and English, you can easily change the language of tutorials using menu .

This app for watching Python tutorials for learning Python programming language.This app providing the functionality for easy to learn and working with very powerful and simple programming language Python. In this app we are providing two language tutorials Hindi and English, you can easily change the language of tutorials using menu .

The NumPy module of Python provides a function called NumPy.histogram(). This function represents the frequency of the number of values that are compared with a set of values ranges.

Among the plethora of programming languages we have today, most of the programmers prefer Python. The reason for this is the emphasis Python gives on the readability and efficiency of the code they write. In general, we can brief Python as an object-oriented language developed in the 1980s by Dutchman Guido van Rossum. The tech giants like IBM, Cisco, Google, Quora, Dropbox, etc. use Python due to its simplicity and elegance.

Being one of the strongest and the most dynamic programming languages of these days, Python is favorable for web and desktop app development, and scientific, data-driven and AI app developments.

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NumPy ndarray objects can be indexed using Python x[selection_obj] syntax, where x is the array. There are three kinds of indexing available in numpy: field access, basic slicing, advanced indexing.

Python provides some special function having __ as prefix and suffix in the name, which is also known as Magic method or Dunder method. This function is automatically invoked when the associated operator is used.

The NumPy sum() function is used to compute sum of array elements over a given axis. The function calculates sum of all elements present in the array by default, otherwise over the specified axis.

The NumPy reshape() function is used to give a new shape to an array without changing its data.

The NumPy package contains matlib module. This module contains all the functions in the numpy namespace that return matrices instead of ndarray objects.

The NumPy package contains a number of functions which provides all the functionality required for linear algebra. Few of these functions are - dot(), vdot(), inner(), matmul(), det(), solve() and inv().

Array attributes reflect information that is intrinsic to the array. Accessing an array through its attributes allows to get and sometimes set intrinsic properties of the array without creating a new array.

The NumPy package contains a number of functions which can be used to create an array from an existing data. asarray(), frombuffer() and fromiter() fuctions.

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